Transformation-based Framework for the Evaluation and Improvement of Database Schemas

Data schemas are primary artefacts for the development and maintenance of data intensive software systems. As for the application code, one way to improve the quality of the models is to ensure that they comply with best design practices. In this paper, we redefine the process of schema quality evaluation as the identification of specific schema construct and their comparison with best practices. We provide an overview of a framework based on the use of semantics-preserving transformations as a way to identify, compare and suggest improvement for the most significant best design practices. The validation and the automation of the framework are discussed and some clarifying examples are provided.